Research on the environment, health, and well-being nexus (EHWB) is shifting from a silo toward a systemic approach that includes the socio-economic context. To disentangle further the complex interplay between the socio-exposome and internal chemical exposure, we performed a meta-analysis of human biomonitoring (HBM) studies with internal exposure data on per-and polyfluoroalkyl substances (PFASs) and detailed information on risk factors, including descriptors of socio-economic status (SES) of the study population. PFASs are persistent in nature, and some have endocrine-disrupting properties. Individual studies have shown that HBM biomarker concentrations of PFASs generally increase with SES indicators, e.g., for income. Based on a meta-analysis (five studies) of the associations between PFASs and SES indicators, the magnitude of the association could be estimated. For the SES indicator income, changes in income were expressed by a factor change, which was corrected by the Gini coefficient to take into account the differences in income categories between studies, and the income range between countries. For the SES indicator education, we had to conclude that descriptors (<college, x years of study, etc.) differed too widely between studies to perform a meta-analysis. Therefore, the use of the uniform ISCED (International Standard Classification of Education) is recommended in future studies. The meta-analysis showed that a higher income is associated with a higher internal exposure to PFASs (PFOS or perfluorooctanesulfonic acid, PFOA or perfluorooctanoic acid, PFNA or perfluorononanoic acid, PFHxS or perfluorohexane sulfonate). This is opposite to the environmental justice hypothesis, referring to an inequitable distribution of detrimental environmental effects toward poor and minority communities by a practice or policy. With a doubling of the income, internal exposure increased on average by 10%–14%. Possible explanations for this difference are given, e.g., underlying differences in diet. However, other sources can also contribute, and the exact causes of SES-related differences in PFAS concentrations remain unclear. Studies are needed that include social descriptors together with lifestyle and dietary information as explanatory variables for internal chemical exposure levels. This will help clarify the underlying factors that link SES with inequity to environmental exposures, and will raise awareness and knowledge to strengthen the capacities of people and communities to advocate chemical exposure reduction in order to reduce this health inequity.

The European Union’s 7th Environmental Action Programme (EAP) aims to assess and minimize environmental health risks from the use of hazardous chemicals by 2020. From this angle, policy questions like whether an implemented policy to reduce chemical exposure has had an effect over time, whether the health of people in specific regions or subpopulations is at risk, or whether the body burden of chemical substances (the internal exposure) varies with, for example, time, country, sex, age, or socio-economic status, need to be answered. Indicators can help to synthesize complex scientific information into a few key descriptors with the purpose of providing an answer to a non-expert audience. Human biomonitoring (HBM) indicators at the European Union (EU) level are unfortunately lacking. Within the Horizon2020 European Human Biomonitoring project HBM4EU, an approach to develop European HBM indicators was worked out. To learn from and ensure interoperability with other European indicators, 15 experts from the HBM4EU project (German Umweltbundesamt (UBA), Flemish research institute VITO, University of Antwerp, European Environment Agency (EEA)), and the World Health Organization (WHO), European Core Health Indicator initiative (ECHI), Eurostat, Swiss ETH Zurich and the Czech environmental institute CENIA, and contributed to a workshop, held in June 2017 at the EEA in Copenhagen. First, selection criteria were defined to evaluate when and if results of internal chemical exposure measured by HBM, need to be translated into a European HBM-based indicator. Two main aspects are the HBM indicator’s relevance for policy, society, health, and the quality of the biomarker data (availability, comparability, ease of interpretation). Secondly, an approach for the calculation of the indicators was designed. Two types of indicators were proposed: ‘sum indicators of internal exposure’ derived directly from HBM biomarker concentrations and ‘indicators for health risk’, comparing HBM concentrations to HBM health-based guidance values (HBM HBGVs). In the latter case, both the percentage of the studied population exceeding the HBM HBGVs (PE) and the extent of exceedance (EE), calculated as the population’s exposure level divided by the HBM HBGV, can be calculated. These indicators were applied to two examples of hazardous chemicals: bisphenol A (BPA) and per- and polyfluoroalkyl substances (PFASs), which both have high policy and societal relevance and for which high quality published data were available (DEMOCOPHES, Swedish monitoring campaign). European HBM indicators help to summarize internal exposure to chemical substances among the European population and communicate to what degree environmental policies are successful in keeping internal exposures sufficiently low. The main aim of HBM indicators is to allow follow-up of chemical safety in Europe.

Currently used pesticides are rapidly metabolised and excreted, primarily in urine, and urinary concentrations of pesticides/metabolites are therefore useful biomarkers for the integrated exposure from all sources. Pyrethroid insecticides, the organophosphate insecticide chlorpyrifos, and the herbicide glyphosate, were among the prioritised substances in the HBM4EU project and comparable human biomonitoring (HBM)-data were obtained from the HBM4EU Aligned Studies. The aim of this review was to supplement these data by presenting additional HBM studies of the priority pesticides across the HBM4EU partner countries published since 2000. We identified relevant studies (44 for pyrethroids, 23 for chlorpyrifos, 24 for glyphosate) by literature search using PubMed and Web of Science. Most studies were from the Western and Southern part of the EU and data were lacking from more than half of the HBM4EU-partner countries. Many studies were regional with relatively small sample size and few studies address residential and occupational exposure. Variation in urine sampling, analytical methods, and reporting of the HBM-data hampered the comparability of the results across studies. Despite these shortcomings, a widespread exposure to these substances in the general EU population with marked geographical differences was indicated. The findings emphasise the need for harmonisation of methods and reporting in future studies as initiated during HBM4EU.

Regulating chemical mixtures is a complex scientific and policy task. The aim of this study was to investigate typical mixtures and their potential risks based on internal exposure levels in the European population. Based on human biomonitoring (HBM) data made available via the HBM4EU project, we derived generic mixtures representative of a median (P50) and a worst-case scenario (P95) for adults and children. We performed a mixture risk assessment based on HBM concentrations, health-based guidance values (HBGVs) as internal thresholds of concern, and the conservative assumption of concentration addition applied across different toxicological endpoints. Maximum cumulative ratios (MCRs) were calculated to characterize the mixture risk. The mixtures comprise 136 biomarkers for adults and 84 for children, although concentration levels could be quantified only for a fraction of these. Due to limited availability of HBGVs, the mixture risk was assessed for a subset of 20 substance-biomarker pairs for adults and 17 for children. The mixture hazard index ranged from 2.8 (P50, children) to 9.2 (P95, adults). Six to seven substances contributed to over 95% of the total risk. MCR values ranged between 2.6 and 5.5, which is in a similar range as in previous studies based on human external exposures assessments. The limited coverage of substances included in the calculations and the application of a hazard index across toxicological endpoints argue for caution in the interpretation of the results. Nonetheless the analyses of MCR and MAF_ceiling can help inform a possible mixture assessment factor (MAF) applicable to single substance risk assessment to account for exposure to unintentional mixtures.

The European Joint Programme HBM4EU coordinated and advanced human biomonitoring (HBM) in Europe in order to provide science-based evidence for chemical policy development and improve chemical management. Arsenic (As) was selected as a priority substance under the HBM4EU initiative for which open, policy relevant questions like the status of exposure had to be answered. Internal exposure to inorganic arsenic (iAs), measured as Toxic Relevant Arsenic (TRA) (the sum of As(III), As(V), MMA, DMA) in urine samples of teenagers differed among the sampling sites (BEA (Spain) > Riksmaten adolescents (Sweden), ESTEBAN (France) > FLEHS IV (Belgium), SLO CRP (Slovenia)) with geometric means between 3.84 and 8.47 μg/L. The ratio TRA to TRA + arsenobetaine or the ratio TRA to total arsenic varied between 0.22 and 0.49. Main exposure determinants for TRA were the consumption of rice and seafood. When all studies were combined, Pearson correlation analysis showed significant associations between all considered As species. Higher concentrations of DMA, quantitatively a major constituent of TRA, were found with increasing arsenobetaine concentrations, a marker for organic As intake, e.g. through seafood, indicating that other sources of DMA than metabolism of inorganic As exist, e.g. direct intake of DMA or via the intake of arsenosugars or -lipids. Given the lower toxicity of DMA(V) versus iAs, estimating the amount of DMA not originating from iAs, or normalizing TRA for arsenobetaine intake could be useful for estimating iAs exposure and risk. Comparing urinary TRA concentrations with formerly derived biomonitoring equivalent (BE) for non-carcinogenic effects (6.4 μg/L) clearly shows that all 95th percentile exposure values in the different studies exceeded this BE. This together with the fact that cancer risk may not be excluded even at lower iAs levels, suggests a possible health concern for the general population of Europe.

Previous studies have shown that toxicity of cationic trace metals in soil is partially confounded by effects of the accompanying anions. A similar assessment is reported here for toxicity of an oxyanion, i.e., molybdate (MoO), the soil toxicity of which is relatively unexplored. Solubility and toxicity were compared between the soluble sodium molybdate (Na₂MoO₄) and the sparingly soluble molybdenum trioxide (MoO₃). Confounding effects of salinity were excluded by referencing the Na₂MoO₄ effect to that of sodium chloride (NaCl). The pH decrease from the acid MoO₃ amendment was equally referenced to a hydrochloric (HCl) treatment or a lime-controlled MoO₃ treatment. The concentrations of molybdenum (Mo) in soil solution or calcium chloride (CaCl₂) 0.01 M extracts were only marginally affected by either MoO₃ or Na₂MoO₄ as an Mo source after 10 to 13 days of equilibration. Effects of Mo on soil nitrification were fully confounded by associated changes in salinity or pH. Effects of Mo on growth of wheat seedlings (Triticum aestivum L) were more pronounced than those on nitrification, and toxicity thresholds were unaffected by the form of added Mo. The Mo thresholds for wheat growth were not confounded by pH or salinity at incipient toxicity. It is concluded that oxyanion toxicity might be confounded in relatively insensitive tests for which reference treatments should be included. Environ. Toxicol. Chem. 2010;29:1274–1278. © 2010 SETAC